ANALYSIS OF MOROCCAN STUDENT PERFORMANCE IN ELECTRICITY IN CORRELATION WITH MATHEMATICS AND FRENCH BY THE MULTIPLE CORRESPONDENCE ANALYSIS METHOD: CASE OF IBN TOFAIL UNIVERSITY

Abstract

This study focuses on the statistical analysis of the performance of students of different ages in solving electricity problems, after learning Physical Matter Sciences (PMS), Chemical Matter Sciences (CMS), Mathematical Sciences and Applications (MSA) and Mathematical and Computer Sciences (MCS) programs in the first year at Ibn Tofail University in Morocco. The student’s scores were obtained in mathematics (analysis and algebra), French, and electricity exams in terms of the 2017/2018 year. The data collected from the written student responses in the electricity exams were analyzed by SPSS software (version 25) using the multiple correspondence analysis method to study the influence of diverse variables: gender (M/F), age, and performance in analysis, algebra and French. The Cronbach's alpha coefficient (0.81) reflects the consistency and reliability of the used method, where 50% of the variability is explained by Dimension 1, and 36% is explained by Dimension 2. The discussion is made on the basis of previous studies conducted in secondary and university cycles of various contexts. It was found that students who perform better in solving electricity problems do not necessarily have a high level in the French teaching language. The teaching language correlates weakly with students' performance in solving electricity problems and their learning electrical concepts and phenomena. A positive correlation between performance in mathematics, particularly algebra, and performance in electricity is confirmed as stated elsewhere. So, the learning electricity at the university level cannot be done without deep mathematical knowledge. The analysis showed that the performance in electricity was not affected by the gender and age of the students.